{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Unmet targets workflow  \n",
    "\n",
    "This notebook outlines the steps to identify possible reasons why the targets were not met to help guide the user to take an appropriate action in each case\n",
    "\n",
    "### Identify unmet targets: \n",
    "REQUIREMENTS:  \n",
    "    File **'output_mvbest.csv'**, columns 'Target Met' + 'MPM' (Minimum Proportion Met)\n",
    "\n",
    "### Worflow for unmet solutions:\n",
    "    If the feature is not met but by very little --> mark as met or decrease MISSLEVEL \n",
    "    Else:\n",
    "        If the feature is in locked-out planning units --> Send warning/mark as met/rethink problem\n",
    "        Else:\n",
    "            If the feature is in a high cost area --> Increase SPF\n",
    "            Else:\n",
    "                The feature has low range and/or is isolated --> Increase SPF\n",
    "                \n",
    "PARAMETERS:  \n",
    "* **threshold met**: when to consider a target as met (by default the misslevel set at input.dat)--> number between 0-1  \n",
    "* **lock_out_limit**: max percentage of the feature pu's that are in locked out areas that trigger response --> number between 0-1 \n",
    "* **high_cost_quantile**: value to define what is high cost (quatile is used to generalize any cost values) --> number between 0-1 \n",
    "* **hcost_limit**: max percentage of the feature pu's that are in high cost areas that trigger response --> number between 0-1 \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%run marxan_utils.ipynb "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Helper functions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "def locatePU(MARXAN_FOLDER:str,MARXAN_INPUTDATA:str,pus_of_interest=None, feature=None) -> dict:\n",
    "    \"\"\" Check if feature is in an area of interest\n",
    "    \"\"\"\n",
    "    userInputFile = readInput(MARXAN_FOLDER,MARXAN_INPUTDATA)\n",
    "    puvsp = validateFile(MARXAN_FOLDER,MARXAN_INPUTDATA, planningUnitVSConservationFeatureV)\n",
    "    \n",
    "    feature_in_pu=puvsp[(puvsp['species']==feature) & (puvsp.pu.isin(pus_of_interest))]\n",
    "    \n",
    "    if len(feature_in_pu)== 0: \n",
    "        percentage_in_pu = 0\n",
    "    else:\n",
    "        amount_total = puvsp[puvsp['species']==feature].groupby(['species']).sum('amount').reset_index().amount.values[0]\n",
    "        amount_in_pu= feature_in_pu.groupby('species').sum('amount').reset_index().amount.values[0]\n",
    "        percentage_in_pu = round((amount_in_pu/amount_total)*100,2)\n",
    "    return percentage_in_pu\n",
    "\n",
    "def unmetDecisionTree(MARXAN_FOLDER, MARXAN_INPUTDATA,\n",
    "                      lock_out_limit=0.5, \n",
    "                      high_cost_quantile= 0.7, \n",
    "                      hcost_limit=0.2):\n",
    "    \n",
    "    \"\"\"Follow the decision flow:\n",
    "    - Check if the target is missed by little (already considering the defined misslevel)\n",
    "    - Check if the feature is in a locked-out area \n",
    "    - Check if the feature is in a high cost area\n",
    "    - Check if the feature is very isolated or the range of the feature is very small\n",
    "    \n",
    "    Parameteres:\n",
    "    - threshold met: when to consider a target as met (dy default the misslevel set at input.dat)\n",
    "    - lock_out_limit: amount of the feature pu's that are in locked out areas that trigger response\n",
    "    - high_cost_quantile: decide what is high cost\n",
    "    - hcost_limit: amount of the feature pu's that are in high cost areas that trigger response\n",
    "    \"\"\"\n",
    "    \n",
    "    # Validate and read files\n",
    "    userInputFile = readInput(MARXAN_FOLDER,MARXAN_INPUTDATA)\n",
    "    pu = validateFile(MARXAN_FOLDER,MARXAN_INPUTDATA, planningUnits)\n",
    "    puvsp = validateFile(MARXAN_FOLDER,MARXAN_INPUTDATA, planningUnitVSConservationFeatureV)\n",
    "    mvbest= validateFile(MARXAN_FOLDER,MARXAN_INPUTDATA, OutputMV)\n",
    "    \n",
    "    df = mvbest[['Conservation_Feature','Target_Met','MPM']].copy()\n",
    "    threshold_met = userInputFile.MISSLEVEL\n",
    "    \n",
    "    if len(df.loc[df['Target_Met']=='no','Conservation_Feature'])==0:\n",
    "        unmet = {'None':'All targets met'}\n",
    "    else: \n",
    "        for feature in list(df.loc[df['Target_Met']=='no','Conservation_Feature'].values):\n",
    "        \n",
    "            # 1. Close to target \n",
    "            # Solution: \n",
    "            # - Mark as met: Modify output_mvbest.csv (Target Met) MPM: minimum proportion met\n",
    "            # - Decrease MISSLEVEL (input.dat)\n",
    "            if (df.loc[df['Conservation_Feature']==feature,'MPM']>=threshold_met-(threshold_met*1/100)).bool():\n",
    "                df.loc[df['Conservation_Feature']==feature,'Eval']='Close to target (1% away of misslevel)'\n",
    "\n",
    "            else:\n",
    "        \n",
    "            # 2. In lock-out areas (re-think problem)\n",
    "            # Solution: \n",
    "            # - Rethink problem (Assume not met)\n",
    "            # - Unblock lock-out pu: Modifir pu.dat (status)\n",
    "        \n",
    "                pu_excluded = list(pu[pu['status']==3].id) \n",
    "                excluded_per = locatePU(MARXAN_FOLDER,MARXAN_INPUTDATA,pus_of_interest=pu_excluded, feature=feature)/100\n",
    "                if excluded_per > lock_out_limit: df.loc[df['Conservation_Feature']==feature,'Eval'] = f'{excluded_per*100} % in locked-out areas'\n",
    "            \n",
    "                else:\n",
    "                        \n",
    "            # 3. In high cost areas (increase SPF)\n",
    "            # Solution: \n",
    "            # - Increase SPF: Modify spec.dat (spf)\n",
    "        \n",
    "                    pu_hcost = list(pu[pu['cost']>pu['cost'].quantile([high_cost_quantile], interpolation='nearest').values[0]].id)\n",
    "                    hcost_per = locatePU(MARXAN_FOLDER,MARXAN_INPUTDATA,pus_of_interest=pu_excluded, feature=feature)/100\n",
    "                    if hcost_per > hcost_limit: df.loc[df['Conservation_Feature']==feature,'Eval'] = f'{hcost_per*100} % in high cost areas'\n",
    "                \n",
    "                    else:\n",
    "        \n",
    "            # 4. Small range or isolated \n",
    "            # Solution:\n",
    "            # - Increase SPF: Modify spec.dat (spf)\n",
    "                        feat_range = round(puvsp[puvsp['species']==feature].count().pu/len(pu)*100,2)\n",
    "                        df.loc[df['Conservation_Feature']==feature,'Eval'] = f'Small range ({feat_range} % of planning area) or isolated'     \n",
    "        \n",
    "            unmet = dict(zip(df[df['Target_Met']=='no'].Conservation_Feature, df[df['Target_Met']=='no'].Eval))\n",
    "    return unmet"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "### Next step is to modify input the files according to this output, and then run marxan again"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Example data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "#MARXAN_FOLDER = '/home/jovyan/work/datasets/raw/Marxan_Targets/example_1_Papua'\n",
    "MARXAN_FOLDER = '/home/jovyan/work/datasets/raw/demo_Papua_New_Guinea/marxan_Papua_New_Guinea'\n",
    "\n",
    "MARXAN_INPUTDATA = 'input.dat'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = gapAnalysis(MARXAN_FOLDER, 'input.dat')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>target</th>\n",
       "      <th>prop</th>\n",
       "      <th>name</th>\n",
       "      <th>amount_total</th>\n",
       "      <th>amount_target</th>\n",
       "      <th>amount_lock</th>\n",
       "      <th>prop_lock</th>\n",
       "      <th>target_met_pre</th>\n",
       "      <th>Target</th>\n",
       "      <th>Amount_Held</th>\n",
       "      <th>Occurrence_Target</th>\n",
       "      <th>Occurrences_Held</th>\n",
       "      <th>Separation_Target</th>\n",
       "      <th>Separation_Achieved</th>\n",
       "      <th>Target_Met</th>\n",
       "      <th>MPM</th>\n",
       "      <th>prop_best</th>\n",
       "      <th>prop_best_minus_lock</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>83.2</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0</td>\n",
       "      <td>416.0</td>\n",
       "      <td>83.2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>no</td>\n",
       "      <td>83.2</td>\n",
       "      <td>84.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>84.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>yes</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.201923</td>\n",
       "      <td>0.201923</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>27.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0</td>\n",
       "      <td>137.0</td>\n",
       "      <td>27.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>no</td>\n",
       "      <td>27.4</td>\n",
       "      <td>28.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>yes</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.204380</td>\n",
       "      <td>0.204380</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>32.8</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0</td>\n",
       "      <td>164.0</td>\n",
       "      <td>32.8</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>no</td>\n",
       "      <td>32.8</td>\n",
       "      <td>33.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>yes</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.201220</td>\n",
       "      <td>0.201220</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>5.6</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>5.6</td>\n",
       "      <td>14.0</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>yes</td>\n",
       "      <td>5.6</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>yes</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.214286</td>\n",
       "      <td>-0.285714</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>10.6</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>10.6</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.056604</td>\n",
       "      <td>yes</td>\n",
       "      <td>10.6</td>\n",
       "      <td>11.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>yes</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.207547</td>\n",
       "      <td>0.150943</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      ],
      "text/plain": [
       "   id  target  prop  name  amount_total  amount_target  amount_lock  \\\n",
       "0   1    83.2   0.2     0         416.0           83.2          0.0   \n",
       "1   2    27.4   0.2     0         137.0           27.4          0.0   \n",
       "2   3    32.8   0.2     0         164.0           32.8          0.0   \n",
       "3   4     5.6   0.2     0          28.0            5.6         14.0   \n",
       "4   5    10.6   0.2     0          53.0           10.6          3.0   \n",
       "\n",
       "   prop_lock target_met_pre  Target  Amount_Held  Occurrence_Target  \\\n",
       "0   0.000000             no    83.2         84.0                0.0   \n",
       "1   0.000000             no    27.4         28.0                0.0   \n",
       "2   0.000000             no    32.8         33.0                0.0   \n",
       "3   0.500000            yes     5.6          6.0                0.0   \n",
       "4   0.056604            yes    10.6         11.0                0.0   \n",
       "\n",
       "   Occurrences_Held  Separation_Target  Separation_Achieved Target_Met  MPM  \\\n",
       "0              84.0                0.0                  0.0        yes  1.0   \n",
       "1              28.0                0.0                  0.0        yes  1.0   \n",
       "2              33.0                0.0                  0.0        yes  1.0   \n",
       "3               6.0                0.0                  0.0        yes  1.0   \n",
       "4              11.0                0.0                  0.0        yes  1.0   \n",
       "\n",
       "   prop_best  prop_best_minus_lock  \n",
       "0   0.201923              0.201923  \n",
       "1   0.204380              0.204380  \n",
       "2   0.201220              0.201220  \n",
       "3   0.214286             -0.285714  \n",
       "4   0.207547              0.150943  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x1440 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, anx = plt.subplots(nrows=1, ncols=2,figsize=(10,20), constrained_layout=True)\n",
    "plotGap(df, 'Pre-Marxan', anx[0], post_marxan=False)\n",
    "plotGap(df, 'Post-Marxan', anx[1], post_marxan=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "unmet_dict = unmetDecisionTree(MARXAN_FOLDER, MARXAN_INPUTDATA,\n",
    "                      lock_out_limit=0.5, \n",
    "                      high_cost_quantile= 0.7, \n",
    "                      hcost_limit=0.2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{4361690: 'Small range (0.06 % of planning area) or isolated',\n",
       " 4361619: 'Small range (0.09 % of planning area) or isolated',\n",
       " 3351729: 'Small range (0.05 % of planning area) or isolated',\n",
       " 3351696: 'Close to target (1% away of misslevel)',\n",
       " 3351690: 'Small range (0.01 % of planning area) or isolated',\n",
       " 3351309: 'Small range (0.02 % of planning area) or isolated',\n",
       " 3281565: 'Small range (0.0 % of planning area) or isolated',\n",
       " 3281437: 'Small range (0.02 % of planning area) or isolated',\n",
       " 3281316: 'Small range (0.01 % of planning area) or isolated',\n",
       " 3271794: 'Small range (0.04 % of planning area) or isolated',\n",
       " 3271775: 'Small range (0.03 % of planning area) or isolated',\n",
       " 3271633: 'Small range (0.03 % of planning area) or isolated',\n",
       " 3271611: 'Small range (0.0 % of planning area) or isolated',\n",
       " 3271541: 'Small range (0.0 % of planning area) or isolated',\n",
       " 3261701: 'Small range (0.0 % of planning area) or isolated',\n",
       " 3261631: 'Small range (0.01 % of planning area) or isolated',\n",
       " 3261300: 'Small range (0.03 % of planning area) or isolated',\n",
       " 3251784: 'Small range (0.0 % of planning area) or isolated',\n",
       " 2371794: 'Small range (0.0 % of planning area) or isolated',\n",
       " 2231794: 'Close to target (1% away of misslevel)',\n",
       " 2201265: 'Small range (0.0 % of planning area) or isolated',\n",
       " 2191274: 'Small range (0.0 % of planning area) or isolated',\n",
       " 2191247: 'Small range (0.0 % of planning area) or isolated',\n",
       " 2191116: 'Small range (0.0 % of planning area) or isolated',\n",
       " 2181605: 'Small range (0.0 % of planning area) or isolated',\n",
       " 500115: 'Small range (0.04 % of planning area) or isolated',\n",
       " 300414: 'Small range (0.0 % of planning area) or isolated',\n",
       " 300218: 'Small range (0.09 % of planning area) or isolated',\n",
       " 300215: 'Close to target (1% away of misslevel)',\n",
       " 200417: 'Close to target (1% away of misslevel)',\n",
       " 130137: 'Small range (0.0 % of planning area) or isolated',\n",
       " 130135: 'Small range (0.0 % of planning area) or isolated',\n",
       " 100613: 'Small range (0.0 % of planning area) or isolated',\n",
       " 100215: 'Small range (0.0 % of planning area) or isolated',\n",
       " 100214: 'Close to target (1% away of misslevel)',\n",
       " 43211: 'Small range (0.07 % of planning area) or isolated',\n",
       " 40056: 'Small range (0.01 % of planning area) or isolated',\n",
       " 40012: 'Small range (0.02 % of planning area) or isolated',\n",
       " 30075: 'Small range (0.0 % of planning area) or isolated',\n",
       " 22311: 'Small range (0.0 % of planning area) or isolated',\n",
       " 21811: 'Small range (0.0 % of planning area) or isolated',\n",
       " 20055: 'Small range (0.0 % of planning area) or isolated',\n",
       " 20023: 'Small range (0.0 % of planning area) or isolated',\n",
       " 10065: 'Small range (0.0 % of planning area) or isolated'}"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
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    "unmet_dict"
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